• The Journal of Korea Robotics Society
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• v.9 no.1
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• pp.1-10
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• 2014

In recent years, the research of 3D mapping technique in urban environments obtained by mobile robots equipped with multiple sensors for recognizing the robot's surroundings is being studied actively. However, the map generated by simple integration of multiple sensors data only gives spatial information to robots. To get a semantic knowledge to help an autonomous mobile robot from the map, the robot has to convert low-level map representations to higher-level ones containing semantic knowledge of a scene. Given a 3D point cloud of an urban scene, this research proposes a method to recognize the objects effectively using 3D graph model for autonomous mobile robots. The proposed method is decomposed into three steps: sequential range data acquisition, normal vector estimation and incremental graph-based segmentation. This method guarantees the both real-time performance and accuracy of recognizing the objects in real urban environments. Also, it can provide plentiful data for classifying the objects. To evaluate a performance of proposed method, computation time and recognition rate of objects are analyzed. Experimental results show that the proposed method has efficiently in understanding the semantic knowledge of an urban environment.

• ETRI Journal
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• v.45 no.5
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• pp.746-757
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• 2023

This study presents a novel safe landing algorithm for urban drone deliveries. The rapid advancement of drone technology has given rise to various delivery services for everyday necessities and emergency relief efforts. However, the reliability of drone delivery technology is still insufficient for application in urban environments. The proposed approach uses the "landing angle control" method to allow the drone to land vertically and a rapidly exploring random tree-based collision avoidance algorithm to generate safe and efficient vertical landing paths for drones while avoiding common urban obstacles like trees, street lights, utility poles, and wires; these methods allow for precise and reliable urban drone delivery. We verified the approach within a Gazebo simulation operated through ROS using a six-degree-of-freedom drone model and sensors with similar specifications to actual models. The performance of the algorithms was tested in various scenarios by comparing it with that of stateof-the-art 3D path planning algorithms.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.1D
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• pp.111-120
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• 2009

Restructuring urban land use patterns from the motor-oriented to transit-oriented ones is a contemporary trend in urban planning and transportation. It is expected that transforming urban land use patterns to be transit and walking friendly would resolve various urban problems such as heavy energy consumptions, air pollutions, and traffic congestions. Korean cities have much potentials for developing transit-oriented urban environments in terms of its density and civil service levels, but the level of transit usage levels and the environmental quality of cities are not good enough for supporting such transition. The purpose of this study is to analyze the urban transit center areas and identify the problems to be solved to create transit-oriented urban environments. Case studies of four urban transit center areas in Seoul Metropolitan region were conducted to examine the spatial characteristics of urban transit center areas and identify their problems. Development density, land use diversity, walk-ability and transit connectivity were the primary feature of interests.

• Journal of the Korean association of regional geographers
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• v.3 no.2
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• pp.227-253
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• 1997

Twenty-first century will be in the era of culture and art as postmodernims progresses, therefore, geography which is is traditionally concerned with regional study needs to deeply study the culture of region. Regional symbols are clue to identify regional culture which is environments of symbolic space. Especially the study of urban culture come to the needs of times with occurring global city, urban symbols make clear urban culture and urban identity. The aim of this paper is to analyze urban symbols, that is urban songs, urban birds, urban trees, urban flowers to study urban culture in korean cities, urban symbols make clear urban spatial environment which is natural and human, and then, urban symbols make clear urban identity. The analytical results of lyrics of urban songs in the 76 cities of korea include names of mountain, river, sea and place, the names of mountain and river make clear urban identies which is natural and human characteristics, it is environment of symbolic space which brings unity, one body. Especially it is environment of symbolic space which comprise fung-soo(風水) aspects, place names well represent symbolic space. The analytical results of symbolic things, that is urban birds, urban trees, urban flowers in the 78 cities of korea indicate they are gain and gain established, they are also our environments of symbolic space which is curtual settlings of our life, but they are imported not native species but foreign species which have not environment of symbolic space. The results of this paper implicate urban symols should review. because urban symbols fit to our natural and human environments of symbolic space.

• Journal of Auto-vehicle Safety Association
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• v.14 no.3
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• pp.65-70
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• 2022

Lane change in urban environments is a challenge for both human-driving and automated driving due to their complexity and non-linearity. With the recent development of deep-learning, the use of the RNN network, which uses time series data, has become the mainstream in this field. Many researches using RNN show high accuracy in highway environments, but still do not for urban environments where the surrounding situation is complex and rapidly changing. Therefore, this paper proposes a lane change possibility decision network by adopting Attention layer, which is an SOTA in the field of seq2seq. By weighting each time step within a given time horizon, the context of the road situation is more human-like. A total 7D vectors of x, y distances and longitudinal relative speed of side front and rear vehicles, and longitudinal speed of ego vehicle were used as input. A total 5,614 expert data of 4,098 yield cases and 1,516 non-yield cases were used for training, and the performance of this network was tested through 1,817 data. Our network achieves 99.641% of test accuracy, which is about 4% higher than a network using only LSTM in an urban environment. Furthermore, it shows robust behavior to false-positive or true-negative objects.

• Journal of the Semiconductor & Display Technology
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• v.22 no.2
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• pp.112-119
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• 2023

In urban environments, signals of Global Positioning System (GPS) can be blocked and reflected by tall buildings, large vehicles, and complex components of road network. Therefore, the performance of the positioning system using the GPS module in urban areas can be degraded due to the loss of GPS signals necessary for the position estimation. To deal with this issue, various localization schemes using inertial measurement unit (IMU) sensors, such as gyroscope and accelerometer, and Bayesian filters, such as Kalman filter (KF) and particle filter (PF), have been designed to enhance the performance of the GPS-based positioning system. Among Bayesian filters, the PF has been widely used for the target tracking and vehicle navigation, since it can provide superior performance in estimating the state of a dynamic system under nonlinear/non-Gaussian circumstance. This paper presents a positioning system that uses the double-stacked particle filter (DSPF) as well as the accelerometer, gyroscope, and GPS receiver on the smartphone to provide higher pedestrian positioning accuracy in urban environments. The DSPF employs a nonparametric technique (Parzen-window) to create the multimodal target distribution that approximates the posterior distribution. Experimental results show that the DSPF-based positioning system can provide the significant improvement of the pedestrian position estimation in urban environments.

• Journal of Korean Society for Atmospheric Environment
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• v.34 no.5
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• pp.697-707
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• 2018

A fast running model comprising the climate change effects is proposed for urban heat environment simulations so as to be used in urban heat island studies and/or the urban planning practices. By combining Hot City Model, a high resolution urban temperature prediction model utilizing the Lagrangian particle tracing technique, and the numerical weather simulation data which are constructed up to year of 2100 under the climate change scenarios, an efficient model is constructed for simulating the future urban heat environments. It is applicable to whole city as well as to a small block area of an urban region, with the computation time being relatively short, requiring the practically manageable amount of the computational resources. The heat environments of the entire metropolitan Seoul area in South Korea are investigated with the aid of the model for the present time and for the future. The results showed that the urban temperature gradually increase up to a significant level in the future. The possible effects of green roofs on the buildings are also studied, and we observe that green roofs don't lower the urban temperature efficiently while making the temperature fields become more homogeneous.

• Journal of the Korean Institute of Landscape Architecture
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• v.15 no.1
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• pp.69-84
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• 1987

According to the complexity and the pluralism of the modern cities, they are changing themselves into the multinoded and social - classless urban environments. The sudden drift of population to the cities is giving rise to the serious environmental problems, and the rapid increase of recreational needs among the citizen is changing the urban society into a leisure - oriented one. In order to coping with the abrupt change in the social and natural urban environments, the various fields of urban society should be co - ordinated. The study uses the green - city concept to get solves the incongruity of urban structure in Chonju City. The existing open space maps were drawn up by the various techniques such as the analysis of the topographic maps and collected data, the interpretation of the aero-photographs and the reconnaissance of site. The authors suggested the existing condition, and the problems and potentials of open space elements in Chonju City through the analysis of the existing condition maps. After synthesizing the contents of analysis, the 7u(hors established an exclusive open space system for Chonju City.

• Journal of Positioning, Navigation, and Timing
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• v.7 no.4
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• pp.205-215
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• 2018

The recent emergence of new Global Navigation Satellite Systems (GNSS) has resulted in a gradual improvement in the performance of positioning services. This paper verifies the degree of improvement in positioning performance of Assisted-GNSS (A-GNSS) receivers using assistance information compared to standalone-GNSS receivers that do not use assistance information in various urban environments in Korea. For this purpose, field tests are performed in various urban and indoor environments in Korea. The assistance information is provided by u-blox's AssistNow Online and low-cost commercial receivers are used for mobile station receivers. Through experiments, the Time to First Fix (TTFF), acquisition sensitivity, and position accuracy performance improvement are analyzed. The results of the experiments show that using assistance data improved the performance in all experiment locations, and, in particular, a significant performance improvement in terms of TTFF.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.5
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• pp.436-443
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• 2011

Recognition of structures in urban environments is a fundamental ability for unmanned ground vehicles. In this paper we propose the geometrical featured voxel which has not only 3-D coordinates but also the type of geometrical properties of point cloud. Instead of dealing with a huge amount of point cloud collected by range sensors in urban, the proposed voxel can efficiently represent and save 3-D urban structures without loss of geometrical properties. We also provide an urban structure classification algorithm by using the proposed voxel and machine learning techniques. The proposed method enables to recognize urban environments around unmanned ground vehicles quickly. In order to evaluate an ability of the proposed map representation and the urban structure classification algorithm, our vehicle equipped with the sensor system collected range data and pose data in campus and experimental results have been shown in this paper.